We aim to determine the accuracy and specificity of Arterial spin labeling (ASL) — a non‐invasive perfusion technique used in MRI to track cerebral blood flow — in measuring vascular and glial‐dependent water transfer to establish whether it is a valuable clinical tool in Alzheimer’s disease. This simple and safe technique, already approved for use in a clinical setting, has potential to circumvent current invasive approaches in human subjects at risk for AD‐related dementias.
Targeted Condition: Cognitive Disorders
Disseminating a user-friendly guide: Advancing the science of intervention adaptation and improving access to evidence-based psychological treatment
Adaptation of evidence-based practices and programs (EBPs) is a necessary component of the implementation process. EBPs must be adapted to function with the constraints of real-world practice settings, providers’ expertise, and patients’ needs. The science of intervention adaptation is hungry for well-defined methods of EBP adaptation to guide decision making. A how-to guide for EBP adaptation titled MODIFI: Making Optimal Decisions for Intervention Flexibility during Implementation, is under development with NIMH funding (F32 MH116623). MODIFI will be disseminated via multiple strategies locally, nationally, and internationally. Dissemination of MODIFI will improve the practice of intervention adaptation by providing practitioners with a how-to guide that is (a) evidence-based, (b) usable, and (c) supported by the expert consensus of implementation practitioners and researchers.
Estia: computerized intervention targeting cognitive control deficits in depressed adults
Project: EVO (or “EVO”) is a mobile 3D video game that has been shown to reduce older adults’ susceptibility to interference by augmenting sustained attention and working memory abilities (e.g. cognitive control) through targeted adaptive algorithms. The combination of peer-reviewed validity, adaptivity, and fun video game mechanics elevates the EVO platform beyond other at-home training tools while reducing burden associated with tedious task replication. We propose to study EVO as a potential intervention for the treatment of depression, a disorder that worsens medical outcomes, promotes disability, increases expense, and complicates medical care by clouding the clinical picture and undermining treatment adherence.
